Sjgren-Larsson syndrome (SLS) is a rare inherited neurocutaneous disease characterized by ichthyosis, spastic diplegia or tetraplegia, intellectual disability, and a distinctive retinopathy. It is caused by mutations in ALDH3A2, which codes for fatty aldehyde dehydrogenase (FALDH) and results in abnormal lipid metabolism. Despite knowing the gene defect and enzyme abnormality, the pathogenic mechanisms are still unclear and no single biomarker exists that correlates with disease severity. FALDH deficiency results in several lipid abnormalities including accumulation of fatty aldehydes, which have potential toxic effects via formation of covalent adducts with proteins and lipids. This unusual lipid abnormality has the potential to affect multiple unrelated cellular pathways that are critical for disease pathogenesis. Our recent metabolomic studies in SLS have identified a unique biochemical profile of at least 30 metabolites in plasma that suggests disruption of several previously unsuspected pathways. We now propose to mine our STAIR 7004 clinical database of 20 SLS patients together with their associated metabolomic data to develop a minimal ?metabolomic profile? that will correlate with severity of clinical symptoms and function as a reliable biomarker. These studies will utilize various statistical analytical methods, including principal component analysis, hierarchical clustering and random forest analysis, to define a minimal group of clinically informative metabolites, representing multiple biochemical pathways, for construction of a SLS metabolomic profile. When completed, this research will provide an objective biomarker for SLS disease description and therapeutic monitoring.